code: def _download_fancy_data(self):
      text = """
      An original sentence not subject to any license restrictions, copyright, or royalty payments. Nothing to see here. Commercial or non-commercial use. Research or non-research purposes. The quick brown fox jumps over the lazy dog. Lorem ipsum.
      """
      text = text * 1024
      encoded = text.encode("ascii", "replace")
      ints = [int(encoded[i]) for i in range(len(encoded))]
      return torch.tensor(ints)
  
imports: import torch
  import unittest
  from apex.transformer.testing import global_vars
  from apex.transformer.testing.standalone_bert import bert_model_provider
  from apex.transformer.pipeline_parallel.schedules.common import _get_params_for_weight_decay_optimization, build_model
  from apex.transformer.pipeline_parallel.schedules import get_forward_backward_func
  from apex.transformer.pipeline_parallel.utils import average_losses_across_data_parallel_group, unwrap_model, setup_microbatch_calculator
  from apex.transformer.log_util import set_logging_level
  from apex.transformer import tensor_parallel, parallel_state
  from apex.transformer.enums import ModelType
  from apex.transformer._ucc_util import HAS_UCC
  from apex.transformer.testing.distributed_test_base import UccDistributedTestBase, NcclDistributedTestBase
  import logging
  from torch.testing._internal import common_utils
label_desc: Use image node_id 1 for calling the BertTestBase obj's underlying member method code with example usage: obj._download_fancy_data() and returns: torch